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Zhang T, Ambrodji A, Huang H, Bouchonville KJ, Etheridge AS, Schmidt RE, Bembenek BM, Temesgen ZB, Wang Z, Innocenti F, Stroka D, Diasio RB, Largiadèr CR, Offer SM. Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase ( DPYD). eLife 2024; 13:RP94075. [PMID: 38686795 PMCID: PMC11060711 DOI: 10.7554/elife.94075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024] Open
Abstract
Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome-edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.
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Affiliation(s)
- Ting Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Alisa Ambrodji
- Department of Clinical Chemistry, Inselspital, Bern University Hospital, University of BernBernSwitzerland
- Graduate School for Cellular and Biomedical Sciences, University of BernBernSwitzerland
| | - Huixing Huang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Kelly J Bouchonville
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Amy S Etheridge
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina at Chapel HillChapel HillUnited States
| | - Remington E Schmidt
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Brianna M Bembenek
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Zoey B Temesgen
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Zhiquan Wang
- Division of Hematology, Department of Medicine, Mayo ClinicRochesterUnited States
| | - Federico Innocenti
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina at Chapel HillChapel HillUnited States
| | - Deborah Stroka
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Robert B Diasio
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
| | - Carlo R Largiadèr
- Department of Clinical Chemistry, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Steven M Offer
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo ClinicRochesterUnited States
- Department of Pathology, University of Iowa Carver College of Medicine, University of IowaIowa CityUnited States
- Holden Comprehensive Cancer Center, University of Iowa Carver College of Medicine, University of IowaIowa CityUnited States
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Pandey GK, Vadlamudi S, Currin KW, Moxley AH, Nicholas JC, McAfee JC, Broadaway KA, Mohlke KL. Liver regulatory mechanisms of noncoding variants at lipid and metabolic trait loci. HGG ADVANCES 2024; 5:100275. [PMID: 38297830 PMCID: PMC10881423 DOI: 10.1016/j.xhgg.2024.100275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 02/02/2024] Open
Abstract
Genome-wide association studies (GWASs) have identified hundreds of risk loci for liver disease and lipid-related metabolic traits, although identifying their target genes and molecular mechanisms remains challenging. We predicted target genes at GWAS signals by integrating them with molecular quantitative trait loci for liver gene expression (eQTL) and liver chromatin accessibility QTL (caQTL). We predicted specific regulatory caQTL variants at four GWAS signals located near EFHD1, LITAF, ZNF329, and GPR180. Using transcriptional reporter assays, we determined that caQTL variants rs13395911, rs11644920, rs34003091, and rs9556404 exhibit allelic differences in regulatory activity. We also performed a protein binding assay for rs13395911 and found that FOXA2 differentially interacts with the alleles of rs13395911. For variants rs13395911 and rs11644920 in putative enhancer regulatory elements, we used CRISPRi to demonstrate that repression of the enhancers altered the expression of the predicted target and/or nearby genes. Repression of the element at rs13395911 reduced the expression of EFHD1, and repression of the element at rs11644920 reduced the expression of LITAF, SNN, and TXNDC11. Finally, we showed that EFHD1 is a metabolically active gene in HepG2 cells. Together, these results provide key steps to connect genetic variants with cellular mechanisms and help elucidate the causes of liver disease.
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Affiliation(s)
- Gautam K Pandey
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Anne H Moxley
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jayna C Nicholas
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jessica C McAfee
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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3
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Zhang T, Ambrodji A, Huang H, Bouchonville KJ, Etheridge AS, Schmidt RE, Bembenek BM, Temesgen ZB, Wang Z, Innocenti F, Stroka D, Diasio RB, Largiadèr CR, Offer SM. Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase ( DPYD). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.01.565230. [PMID: 37961517 PMCID: PMC10635067 DOI: 10.1101/2023.11.01.565230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.
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Affiliation(s)
- Ting Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Alisa Ambrodji
- Department of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, CH-3010 Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Freiestrasse 1, CH-3010 Bern, Switzerland
| | - Huixing Huang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Kelly J. Bouchonville
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Amy S. Etheridge
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Remington E. Schmidt
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Brianna M. Bembenek
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Zoey B. Temesgen
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Zhiquan Wang
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN 55905 USA
| | - Federico Innocenti
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Deborah Stroka
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Robert B. Diasio
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Carlo R. Largiadèr
- Department of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, CH-3010 Bern, Switzerland
| | - Steven M. Offer
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
- Department of Pathology, University of Iowa Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
- Holden Comprehensive Cancer Center, University of Iowa Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
- Lead contact
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Jia K, Shen J. Transcriptome-wide association studies associated with Crohn's disease: challenges and perspectives. Cell Biosci 2024; 14:29. [PMID: 38403629 PMCID: PMC10895848 DOI: 10.1186/s13578-024-01204-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/04/2024] [Indexed: 02/27/2024] Open
Abstract
Crohn's disease (CD) is regarded as a lifelong progressive disease affecting all segments of the intestinal tract and multiple organs. Based on genome-wide association studies (GWAS) and gene expression data, transcriptome-wide association studies (TWAS) can help identify susceptibility genes associated with pathogenesis and disease behavior. In this review, we overview seven reported TWASs of CD, summarize their study designs, and discuss the key methods and steps used in TWAS, which affect the prioritization of susceptibility genes. This article summarized the screening of tissue-specific susceptibility genes for CD, and discussed the reported potential pathological mechanisms of overlapping susceptibility genes related to CD in a certain tissue type. We observed that ileal lipid-related metabolism and colonic extracellular vesicles may be involved in the pathogenesis of CD by performing GO pathway enrichment analysis for susceptibility genes. We further pointed the low reproducibility of TWAS associated with CD and discussed the reasons for these issues, strategies for solving them. In the future, more TWAS are needed to be designed into large-scale, unified cohorts, unified analysis pipelines, and fully classified databases of expression trait loci.
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Affiliation(s)
- Keyu Jia
- Laboratory of Medicine, Baoshan Branch, Ren Ji Hospital, School of Medicine, Nephrology department, Shanghai Jiao Tong University, 1058 Huanzhen Northroad, Shanghai, 200444, China
| | - Jun Shen
- Laboratory of Medicine, Baoshan Branch, Ren Ji Hospital, School of Medicine, Nephrology department, Shanghai Jiao Tong University, 1058 Huanzhen Northroad, Shanghai, 200444, China.
- Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Inflammatory Bowel Research Center, Ren Ji Hospital, School of Medicine, Shanghai Institute of Digestive Disease, Shanghai Jiao Tong University, Shanghai, China.
- NHC Key Laboratory of Digestive Diseases, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
- Division of Gastroenterology and Hepatology, Baoshan Branch, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
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Zhang Y, Zhu Z, Sun L, Yin W, Liang Y, Chen H, Bi Y, Zhai W, Yin Y, Zhang W. Hepatic G Protein-Coupled Receptor 180 Deficiency Ameliorates High Fat Diet-Induced Lipid Accumulation via the Gi-PKA-SREBP Pathway. Nutrients 2023; 15:1838. [PMID: 37111058 PMCID: PMC10144310 DOI: 10.3390/nu15081838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/09/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Single-nucleotide polymorphisms in G protein-coupled receptor 180 (GPR180) are associated with hypertriglyceridemia. The aim of this study was to determine whether hepatic GPR180 impacts lipid metabolism. Hepatic GPR180 was knocked down using two approaches: Gpr180-specific short hairpin (sh)RNA carried by adeno-associated virus 9 (AAV9) and alb-Gpr180-/- transgene established by crossbreeding albumin-Cre mice with Gpr180flox/flox animals, in which Gpr180 was specifically knocked down in hepatocytes. Adiposity, hepatic lipid contents, and proteins related to lipid metabolism were analyzed. The effects of GPR180 on triglyceride and cholesterol synthesis were further verified by knocking down or overexpressing Gpr180 in Hepa1-6 cells. Gpr180 mRNA was upregulated in the liver of HFD-induced obese mice. Deficiency of Gpr180 decreased triglyceride and cholesterol contents in the liver and plasma, ameliorated hepatic lipid deposition in HFD-induced obese mice, increased energy metabolism, and reduced adiposity. These alterations were associated with downregulation of transcription factors SREBP1 and SREBP2, and their target acetyl-CoA carboxylase. In Hepa1-6 cells, Gpr180 knockdown decreased intracellular triglyceride and cholesterol contents, whereas its overexpression increased their levels. Overexpression of Gpr180 significantly reduced the PKA-mediated phosphorylation of substrates and consequent CREB activity. Hence, GPR180 might represent a novel drug target for intervention of adiposity and liver steatosis.
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Affiliation(s)
- Yunhua Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of Medicine, Shihezi 832002, China
| | - Ziming Zhu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Lijun Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Wenzhen Yin
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yuan Liang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Hong Chen
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yanghui Bi
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Wenbo Zhai
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yue Yin
- Department of Pharmacology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China
| | - Weizhen Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
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PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity. J Cheminform 2023; 15:31. [PMID: 36864534 PMCID: PMC9983232 DOI: 10.1186/s13321-023-00701-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 02/17/2023] [Indexed: 03/04/2023] Open
Abstract
Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding affinity and thus impact the drug's efficacy and side effects. Unfortunately, large-scale experimental screening of ligand-binding against protein variants is still time-consuming and expensive. Alternatively, in silico approaches can play a role in guiding those experiments. Methods ranging from computationally cheaper machine learning (ML) to the more expensive molecular dynamics have been applied to accurately predict the mutation effects. However, these effects have been mostly studied on limited and small datasets, while ideally a large dataset of binding affinity changes due to binding site mutations is needed. In this work, we used the PSnpBind database with six hundred thousand docking experiments to train a machine learning model predicting protein-ligand binding affinity for both wild-type proteins and their variants with a single-point mutation in the binding site. A numerical representation of the protein, binding site, mutation, and ligand information was encoded using 256 features, half of them were manually selected based on domain knowledge. A machine learning approach composed of two regression models is proposed, the first predicting wild-type protein-ligand binding affinity while the second predicting the mutated protein-ligand binding affinity. The best performing models reported an RMSE value within 0.5 [Formula: see text] 0.6 kcal/mol-1 on an independent test set with an R2 value of 0.87 [Formula: see text] 0.90. We report an improvement in the prediction performance compared to several reported models developed for protein-ligand binding affinity prediction. The obtained models can be used as a complementary method in early-stage drug discovery. They can be applied to rapidly obtain a better overview of the ligand binding affinity changes across protein variants carried by people in the population and narrow down the search space where more time-demanding methods can be used to identify potential leads that achieve a better affinity for all protein variants.
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Nicoletti P, Dellinger A, Li YJ, Barnhart HX, Chalasani N, Fontana RJ, Odin JA, Serrano J, Stolz A, Etheridge AS, Innocenti F, Govaere O, Grove JI, Stephens C, Aithal GP, Andrade RJ, Bjornsson ES, Daly AK, Lucena MI, Watkins PB. Identification of Reduced ERAP2 Expression and a Novel HLA Allele as Components of a Risk Score for Susceptibility to Liver Injury Due to Amoxicillin-Clavulanate. Gastroenterology 2023; 164:454-466. [PMID: 36496055 PMCID: PMC9974860 DOI: 10.1053/j.gastro.2022.11.036] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/21/2022] [Accepted: 11/28/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND & AIMS Drug-induced liver injury (DILI) due to amoxicillin-clavulanate (AC) has been associated with HLA-A∗02:01, HLA-DRB1∗15:01, and rs2476601, a missense variant in PTPN22. The aim of this study was to identify novel risk factors for AC-DILI and to construct a genetic risk score (GRS). METHODS Transcriptome-wide association study and genome-wide association study analyses were performed on 444 AC-DILI cases and 10,397 population-based controls of European descent. Associations were confirmed in a validation cohort (n = 133 cases and 17,836 population-based controls). Discovery and validation AC-DILI cases were also compared with 1358 and 403 non-AC-DILI cases. RESULTS Transcriptome-wide association study revealed a significant association of AC-DILI risk with reduced liver expression of ERAP2 (P = 3.7 × 10-7), coding for an aminopeptidase involved in antigen presentation. The lead eQTL single nucleotide polymorphism, rs1363907 (G), was associated with AC-DILI risk in the discovery (odds ratio [OR], 1.68; 95% CI, 1.23-1.66; P = 1.7 × 10-7) and validation cohorts (OR, 1.2; 95% CI, 1.04-2.05; P = .03), following a recessive model. We also identified HLA-B∗15:18 as a novel AC-DILI risk factor in both discovery (OR, 4.19; 95% CI, 2.09-8.36; P = 4.9 × 10-5) and validation (OR, 7.78; 95% CI, 2.75-21.99; P = .0001) cohorts. GRS, incorporating rs1363907, rs2476601, HLA-B∗15:18, HLA-A∗02:01, and HLA-DRB1∗15:01, was highly predictive of AC-DILI risk when cases were analyzed against both general population and non-AC-DILI control cohorts. GRS was the most significant predictor in a regression model containing known AC-DILI clinical risk characteristics and significantly improved the predictive model. CONCLUSIONS We identified novel associations of AC-DILI risk with ERAP2 low expression and with HLA-B∗15:18. GRS based on the 5 risk variants may assist AC-DILI causality assessment and risk management.
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Affiliation(s)
- Paola Nicoletti
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York.
| | - Andrew Dellinger
- Duke Molecular Physiology Institute, Duke University, Durham, North Carolina
| | - Yi Ju Li
- Duke Molecular Physiology Institute, Duke University, Durham, North Carolina; Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina
| | - Huiman X Barnhart
- Duke Molecular Physiology Institute, Duke University, Durham, North Carolina; Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina
| | - Naga Chalasani
- Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - Joseph A Odin
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jose Serrano
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Andrew Stolz
- University of Southern California, Los Angeles, California
| | - Amy S Etheridge
- University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Federico Innocenti
- University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Olivier Govaere
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jane I Grove
- Nottingham Digestive Diseases Centre and National Institute for Health Research Nottingham Biomedical Research Centre at the Nottingham University Hospital National Health Service Trust, Nottingham, United Kingdom; University of Nottingham, Nottingham, United Kingdom
| | - Camilla Stephens
- Servicios de Digestivo y Farmacologia Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA_Plataforma Bionand), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain
| | - Guruprasad P Aithal
- Nottingham Digestive Diseases Centre and National Institute for Health Research Nottingham Biomedical Research Centre at the Nottingham University Hospital National Health Service Trust, Nottingham, United Kingdom; University of Nottingham, Nottingham, United Kingdom
| | - Raul J Andrade
- Servicios de Digestivo y Farmacologia Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA_Plataforma Bionand), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain
| | - Einar S Bjornsson
- Department of Internal Medicine, Landspitali University Hospital, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ann K Daly
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - M Isabel Lucena
- Servicios de Digestivo y Farmacologia Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA_Plataforma Bionand), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain
| | - Paul B Watkins
- University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; University of North Carolina Institute for Drug Safety Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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Predicting Dihydropyrimidine Dehydrogenase Deficiency and Related 5-Fluorouracil Toxicity: Opportunities and Challenges of DPYD Exon Sequencing and the Role of Phenotyping Assays. Int J Mol Sci 2022; 23:ijms232213923. [PMID: 36430399 PMCID: PMC9694733 DOI: 10.3390/ijms232213923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/03/2022] [Accepted: 11/09/2022] [Indexed: 11/16/2022] Open
Abstract
Deficiency of dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is associated with severe toxicity induced by the anti-cancer drug 5-Fluorouracil (5-FU). DPYD genotyping of four recommended polymorphisms is widely used to predict toxicity, yet their prediction power is limited. Increasing availability of next generation sequencing (NGS) will allow us to screen rare variants, predicting a larger fraction of DPD deficiencies. Genotype−phenotype correlations were investigated by performing DPYD exon sequencing in 94 patients assessed for DPD deficiency by the 5-FU degradation rate (5-FUDR) assay. Association of common variants with 5-FUDR was analyzed with the SNPStats software. Functional interpretation of rare variants was performed by in-silico analysis (using the HSF system and PredictSNP) and literature review. A total of 23 rare variants and 8 common variants were detected. Among common variants, a significant association was found between homozygosity for the rs72728438 (c.1974+75A>G) and decreased 5-FUDR. Haplotype analysis did not detect significant associations with 5-FUDR. Overall, in our sample cohort, NGS exon sequencing allowed us to explain 42.5% of the total DPD deficiencies. NGS sharply improves prediction of DPD deficiencies, yet a broader collection of genotype−phenotype association data is needed to enable the clinical use of sequencing data.
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9
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A resource for integrated genomic analysis of the human liver. Sci Rep 2022; 12:15151. [PMID: 36071064 PMCID: PMC9452507 DOI: 10.1038/s41598-022-18506-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 08/08/2022] [Indexed: 11/18/2022] Open
Abstract
In this study, we generated whole-transcriptome RNA-Seq from n = 192 genotyped liver samples and used these data with existing data from the GTEx Project (RNA-Seq) and previous liver eQTL (microarray) studies to create an enhanced transcriptomic sequence resource in the human liver. Analyses of genotype-expression associations show pronounced enrichment of associations with genes of drug response. The associations are primarily consistent across the two RNA-Seq datasets, with some modest variation, indicating the importance of obtaining multiple datasets to produce a robust resource. We further used an empirical Bayesian model to compare eQTL patterns in liver and an additional 20 GTEx tissues, finding that MHC genes, and especially class II genes, are enriched for liver-specific eQTL patterns. To illustrate the utility of the resource to augment GWAS analysis with small sample sizes, we developed a novel meta-analysis technique to combine several liver eQTL data sources. We also illustrate its application using a transcriptome-enhanced re-analysis of a study of neutropenia in pancreatic cancer patients. The associations of genotype with liver expression, including splice variation and its genetic associations, are made available in a searchable genome browser.
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Harlow CE, Gandawijaya J, Bamford RA, Martin ER, Wood AR, van der Most PJ, Tanaka T, Leonard HL, Etheridge AS, Innocenti F, Beaumont RN, Tyrrell J, Nalls MA, Simonsick EM, Garimella PS, Shiroma EJ, Verweij N, van der Meer P, Gansevoort RT, Snieder H, Gallins PJ, Jima DD, Wright F, Zhou YH, Ferrucci L, Bandinelli S, Hernandez DG, van der Harst P, Patel VV, Waterworth DM, Chu AY, Oguro-Ando A, Frayling TM. Identification and single-base gene-editing functional validation of a cis-EPO variant as a genetic predictor for EPO-increasing therapies. Am J Hum Genet 2022; 109:1638-1652. [PMID: 36055212 PMCID: PMC9502050 DOI: 10.1016/j.ajhg.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 08/03/2022] [Indexed: 11/30/2022] Open
Abstract
Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are currently under clinical development for treating anemia in chronic kidney disease (CKD), but it is important to monitor their cardiovascular safety. Genetic variants can be used as predictors to help inform the potential risk of adverse effects associated with drug treatments. We therefore aimed to use human genetics to help assess the risk of adverse cardiovascular events associated with therapeutically altered EPO levels to help inform clinical trials studying the safety of HIF-PHIs. By performing a genome-wide association meta-analysis of EPO (n = 6,127), we identified a cis-EPO variant (rs1617640) lying in the EPO promoter region. We validated this variant as most likely causal in controlling EPO levels by using genetic and functional approaches, including single-base gene editing. Using this variant as a partial predictor for therapeutic modulation of EPO and large genome-wide association data in Mendelian randomization tests, we found no evidence (at p < 0.05) that genetically predicted long-term rises in endogenous EPO, equivalent to a 2.2-unit increase, increased risk of coronary artery disease (CAD, OR [95% CI] = 1.01 [0.93, 1.07]), myocardial infarction (MI, OR [95% CI] = 0.99 [0.87, 1.15]), or stroke (OR [95% CI] = 0.97 [0.87, 1.07]). We could exclude increased odds of 1.15 for cardiovascular disease for a 2.2-unit EPO increase. A combination of genetic and functional studies provides a powerful approach to investigate the potential therapeutic profile of EPO-increasing therapies for treating anemia in CKD.
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Affiliation(s)
- Charli E Harlow
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Josan Gandawijaya
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Rosemary A Bamford
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Emily-Rose Martin
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Andrew R Wood
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Peter J van der Most
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen 9713, the Netherlands
| | - Toshiko Tanaka
- Longitudinal Studies Section, Translation Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA; Data Tecnica International, Glen Echo, MD 20812, USA; Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amy S Etheridge
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, USA
| | | | - Robin N Beaumont
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Jessica Tyrrell
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA; Data Tecnica International, Glen Echo, MD 20812, USA; Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
| | - Eleanor M Simonsick
- Longitudinal Studies Section, Translation Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA
| | - Pranav S Garimella
- Division of Nephrology-Hypertension, University of California San Diego, San Diego, CA, USA
| | - Eric J Shiroma
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD 20892, USA
| | - Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen 9713, the Netherlands
| | - Peter van der Meer
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen 9713, the Netherlands
| | - Ron T Gansevoort
- University of Groningen, University Medical Center Groningen, Department of Nephrology, Groningen 9713, the Netherlands
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen 9713, the Netherlands
| | - Paul J Gallins
- Bioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, NC 27695, USA
| | - Dereje D Jima
- Bioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, NC 27695, USA; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27606, USA
| | - Fred Wright
- Bioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, NC 27695, USA
| | - Yi-Hui Zhou
- Bioinformatics Research Center, North Carolina State University, 1 Lampe Drive, Raleigh, NC 27695, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translation Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA
| | | | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Utrecht, Utrecht 3584, the Netherlands
| | | | | | | | - Asami Oguro-Ando
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK.
| | - Timothy M Frayling
- University of Exeter Medical School, University of Exeter, Royal Devon and Exeter NHS Trust, Exeter EX2 5DW, UK.
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Plasma levels of angiopoietin-2, VEGF-A, and VCAM-1 as markers of bevacizumab-induced hypertension: CALGB 80303 and 90401 (Alliance). Angiogenesis 2022; 25:47-55. [PMID: 34028627 PMCID: PMC8611102 DOI: 10.1007/s10456-021-09799-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/15/2021] [Indexed: 02/03/2023]
Abstract
Hypertension is a common toxicity induced by bevacizumab and other antiangiogenic drugs. There are no biomarkers to predict the risk of bevacizumab-induced hypertension. This study aimed to identify plasma proteins related to the function of the vasculature to predict the risk of severe bevacizumab-induced hypertension. Using pretreated plasma samples from 398 bevacizumab-treated patients in two clinical trials (CALGB 80303 and 90401), the levels of 17 proteins were measured via ELISA. The association between proteins and grade 3 bevacizumab-induced hypertension was performed by calculating the odds ratio (OR) from logistic regression adjusting for age, sex, and clinical trial. Using the optimal cut-point of each protein, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for hypertension were estimated. Five proteins showed no difference in levels between clinical trials and were used for analyses. Lower levels of angiopoietin-2 (p = 0.0013, OR 3.41, 95% CI 1.67-7.55), VEGF-A (p = 0.0008, OR 4.25, 95% CI 1.93-10.72), and VCAM-1 (p = 0.0067, OR 2.68, 95% CI 1.34-5.63) were associated with an increased risk of grade 3 hypertension. The multivariable model suggests independent effects of angiopoietin-2 (p = 0.0111, OR 2.71, 95% CI 1.29-6.10), VEGF-A (p = 0.0051, OR 3.66, 95% CI 1.54-9.73), and VCAM-1 (p = 0.0308, OR 2.27, 95% CI 1.10-4.92). The presence of low levels of 2-3 proteins had an OR of 10.06 (95% CI 3.92-34.18, p = 1.80 × 10-5) for the risk of hypertension, with sensitivity of 89.7%, specificity of 53.5%, PPV of 17.3%, and NPV of 97.9%. This is the first study providing evidence of plasma proteins with potential value to predict patients at risk of developing bevacizumab-induced hypertension.Clinical trial registration: ClinicalTrials.gov Identifier: NCT00088894 (CALGB 80303); and NCT00110214 (CALGB 90401).
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12
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Dawed AY, Yee SW, Zhou K, van Leeuwen N, Zhang Y, Siddiqui MK, Etheridge A, Innocenti F, Xu F, Li JH, Beulens JW, van der Heijden AA, Slieker RC, Chang YC, Mercader JM, Kaur V, Witte JS, Lee MTM, Kamatani Y, Momozawa Y, Kubo M, Palmer CN, Florez JC, Hedderson MM, ‘t Hart LM, Giacomini KM, Pearson ER. Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas. Diabetes Care 2021; 44:2673-2682. [PMID: 34607834 PMCID: PMC8669535 DOI: 10.2337/dc21-1152] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/20/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Sulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction. RESEARCH DESIGN AND METHODS As an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions. RESULTS After establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor. CONCLUSIONS We have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.
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Affiliation(s)
- Adem Y. Dawed
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K
| | - Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA
| | - Kaixin Zhou
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K
| | - Nienke van Leeuwen
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger, Danville, PA
| | - Moneeza K. Siddiqui
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K
| | - Amy Etheridge
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Federico Innocenti
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Fei Xu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Josephine H. Li
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | - Joline W. Beulens
- Amsterdam UMC, location VUmc, Department of General Practice, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Amber A. van der Heijden
- Amsterdam UMC, location VUmc, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Roderick C. Slieker
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Amsterdam UMC, location VUmc, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Yu-Chuan Chang
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA
| | - Josep M. Mercader
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | - John S. Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | | | | | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Colin N.A. Palmer
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K
| | - Jose C. Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Monique M. Hedderson
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Leen M. ‘t Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of General Practice Medicine, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Kathleen M. Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA
| | - Ewan R. Pearson
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, U.K
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13
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Lu H, Jiang H, Yang S, Li C, Li C, Shao R, Zhang P, Wang D, Liu Z, Qi H, Cai Y, Xu W, Bao X, Wang H, Li L. Trans-eQTLs of the CYP3A4 and CYP3A5 associated with tacrolimus trough blood concentration in Chinese renal transplant patients. Biomed Pharmacother 2021; 145:112407. [PMID: 34781138 DOI: 10.1016/j.biopha.2021.112407] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 09/23/2021] [Accepted: 11/03/2021] [Indexed: 12/15/2022] Open
Abstract
This study aimed to systematically investigate trans-eQTLs of CYP3A4 and CYP3A5 affecting tacrolimus trough blood concentrations in Chinese renal transplant patients. We used Plink v1.90 to perform data quality control and linear regression analysis on GTEx v8 data. SNPs with p-value < 0.05 were selected and the GTEx eQTL Calculator was used to further prioritize the eQTLs of CYP3A4 and CYP3A5 in the liver and small intestine. The eQTLs with a p-value < 5 × 10-5 and MAF≥ 0.05 in the CHB population were selected as candidate eQTLs. The genotyping of candidate eQTLs was performed using high-resolution melting (HRM) assays and Sanger DNA sequencing. This study included 845 Chinese renal transplant patients who received tacrolimus as an immunosuppressive agent. Association between 103 candidate eQTLs and log-transformed tacrolimus concentration/dose ratio (log (C0/D)) in this cohort was conducted using the SNPassoc package of R software. In the end, a total of 75,632 liver eQTLs of CYP3A4, 69,558 liver eQTLs of CYP3A5, 48,596 small intestine eQTLs of CYP3A4 and 28,616 small intestine eQTLs of CYP3A5 were obtained using the GTEx v8 eQTL Calculator. Of the 103 candidate eQTLs, rs75727207, rs181294422 and rs28522676 were significantly associated with tacrolimus log(C0/D) in different genetic models. We discovered a substantial number of novel eQTLs of CYP3A4 and CYP3A5 in liver and small intestine, also found that rs75727207, rs181294422 and rs28522676 may affect tacrolimus trough blood concentrations in Chinese renal transplant patients.
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Affiliation(s)
- Huijie Lu
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Haixia Jiang
- Department of Clinical Laboratory, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Siyao Yang
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Chengcheng Li
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Chuanjiang Li
- Division of Hepatobiliopancreatic Surgery, Department of General Surgery,Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Ruifan Shao
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Pai Zhang
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Daoyi Wang
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Zhiwei Liu
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Huana Qi
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Yinuan Cai
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Wenbin Xu
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Xiaojie Bao
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Hailan Wang
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Liang Li
- Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China; Experimental Education and Administration Center, School of Basic Medical Science, Southern Medical University, Guangzhou 510515, China.
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14
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Griswold AJ, Correa D, Kaplan LD, Best TM. Using Genomic Techniques in Sports and Exercise Science: Current Status and Future Opportunities. Curr Sports Med Rep 2021; 20:617-623. [PMID: 34752437 DOI: 10.1249/jsr.0000000000000908] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
ABSTRACT The past two decades have built on the successes of the Human Genome Project identifying the impact of genetics and genomics on human traits. Given the importance of exercise in the physical and psychological health of individuals across the lifespan, using genomics to understand the impact of genes in the sports medicine field is an emerging field. Given the complexity of the systems involved, high-throughput genomics is required to understand genetic variants, their functions, and ultimately their effect on the body. Consequently, genomic studies have been performed across several domains of sports medicine with varying degrees of success. While the breadth of these is great, they focus largely on the following three areas: 1) performance; 2) injury susceptibility; and 3) sports associated chronic conditions, such as osteoarthritis. Herein, we review literature on genetics and genomics in sports medicine, offer suggestions to bolster existing studies, and suggest ways to ideally impact clinical care.
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Affiliation(s)
| | | | - Lee D Kaplan
- Department of Orthopedic Surgery, UHealth Sports Medicine Institute, University of Miami, Miller School of Medicine, Miami, FL
| | - Thomas M Best
- Department of Orthopedic Surgery, UHealth Sports Medicine Institute, University of Miami, Miller School of Medicine, Miami, FL
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15
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Matthews BJ, Melia T, Waxman DJ. Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model. PLoS Genet 2021; 17:e1009588. [PMID: 34752452 PMCID: PMC8664386 DOI: 10.1371/journal.pgen.1009588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 12/10/2021] [Accepted: 10/27/2021] [Indexed: 12/13/2022] Open
Abstract
Sex differences in gene expression are widespread in the liver, where many autosomal factors act in tandem with growth hormone signaling to regulate individual variability of sex differences in liver metabolism and disease. Here, we compare hepatic transcriptomic and epigenetic profiles of mouse strains C57BL/6J and CAST/EiJ, representing two subspecies separated by 0.5-1 million years of evolution, to elucidate the actions of genetic factors regulating liver sex differences. We identify 144 protein coding genes and 78 lncRNAs showing strain-conserved sex bias; many have gene ontologies relevant to liver function, are more highly liver-specific and show greater sex bias, and are more proximally regulated than genes whose sex bias is strain-dependent. The strain-conserved genes include key growth hormone-dependent transcriptional regulators of liver sex bias; however, three other transcription factors, Trim24, Tox, and Zfp809, lose their sex-biased expression in CAST/EiJ mouse liver. To elucidate the observed strain specificities in expression, we characterized the strain-dependence of sex-biased chromatin opening and enhancer marks at cis regulatory elements (CREs) within expression quantitative trait loci (eQTL) regulating liver sex-biased genes. Strikingly, 208 of 286 eQTLs with strain-specific, sex-differential effects on expression were associated with a complete gain, loss, or reversal of the sex differences in expression between strains. Moreover, 166 of the 286 eQTLs were linked to the strain-dependent gain or loss of localized sex-biased CREs. Remarkably, a subset of these CREs apparently lacked strain-specific genetic variants yet showed coordinated, strain-dependent sex-biased epigenetic regulation. Thus, we directly link hundreds of strain-specific genetic variants to the high variability in CRE activity and expression of sex-biased genes and uncover underlying genetically-determined epigenetic states controlling liver sex bias in genetically diverse mouse populations.
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Affiliation(s)
- Bryan J. Matthews
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
| | - Tisha Melia
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
- Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
| | - David J. Waxman
- Department of Biology, Boston University, Boston, Massachusetts, United States of America
- Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
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16
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Perrin HJ, Currin KW, Vadlamudi S, Pandey GK, Ng KK, Wabitsch M, Laakso M, Love MI, Mohlke KL. Chromatin accessibility and gene expression during adipocyte differentiation identify context-dependent effects at cardiometabolic GWAS loci. PLoS Genet 2021; 17:e1009865. [PMID: 34699533 PMCID: PMC8570510 DOI: 10.1371/journal.pgen.1009865] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/05/2021] [Accepted: 10/07/2021] [Indexed: 12/15/2022] Open
Abstract
Chromatin accessibility and gene expression in relevant cell contexts can guide identification of regulatory elements and mechanisms at genome-wide association study (GWAS) loci. To identify regulatory elements that display differential activity across adipocyte differentiation, we performed ATAC-seq and RNA-seq in a human cell model of preadipocytes and adipocytes at days 4 and 14 of differentiation. For comparison, we created a consensus map of ATAC-seq peaks in 11 human subcutaneous adipose tissue samples. We identified 58,387 context-dependent chromatin accessibility peaks and 3,090 context-dependent genes between all timepoint comparisons (log2 fold change>1, FDR<5%) with 15,919 adipocyte- and 18,244 preadipocyte-dependent peaks. Adipocyte-dependent peaks showed increased overlap (60.1%) with Roadmap Epigenomics adipocyte nuclei enhancers compared to preadipocyte-dependent peaks (11.5%). We linked context-dependent peaks to genes based on adipocyte promoter capture Hi-C data, overlap with adipose eQTL variants, and context-dependent gene expression. Of 16,167 context-dependent peaks linked to a gene, 5,145 were linked by two or more strategies to 1,670 genes. Among GWAS loci for cardiometabolic traits, adipocyte-dependent peaks, but not preadipocyte-dependent peaks, showed significant enrichment (LD score regression P<0.005) for waist-to-hip ratio and modest enrichment (P < 0.05) for HDL-cholesterol. We identified 659 peaks linked to 503 genes by two or more approaches and overlapping a GWAS signal, suggesting a regulatory mechanism at these loci. To identify variants that may alter chromatin accessibility between timepoints, we identified 582 variants in 454 context-dependent peaks that demonstrated allelic imbalance in accessibility (FDR<5%), of which 55 peaks also overlapped GWAS variants. At one GWAS locus for palmitoleic acid, rs603424 was located in an adipocyte-dependent peak linked to SCD and exhibited allelic differences in transcriptional activity in adipocytes (P = 0.003) but not preadipocytes (P = 0.09). These results demonstrate that context-dependent peaks and genes can guide discovery of regulatory variants at GWAS loci and aid identification of regulatory mechanisms. Cardiovascular and metabolic diseases are widespread, and an increased understanding of genetic mechanisms behind these diseases could improve treatment. Chromatin accessibility and gene expression in relevant cell contexts can guide identification of regulatory elements and genetic mechanisms for disease traits. A relevant context for cardiovascular and metabolic disease traits is adipocyte differentiation. To identify regulatory elements and genes that display differences in activity during adipocyte differentiation, we profiled chromatin accessibility and gene expression in a human cell model of preadipocytes and adipocytes. We identified chromatin regions that change accessibility during differentiation and predicted genes they may affect. We also linked these chromatin regions to genetic variants associated with risk of disease. At one genomic region linked to fatty acids, a chromatin region more accessible in adipocytes linked to a fatty acid synthesis gene and exhibited allelic differences in transcriptional activity in adipocytes but not preadipocytes. These results demonstrate that chromatin regions and genes that change during cell context can guide discovery of regulatory variants and aid identification of disease mechanisms.
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Affiliation(s)
- Hannah J. Perrin
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kevin W. Currin
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Swarooparani Vadlamudi
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Gautam K. Pandey
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kenneth K. Ng
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Martin Wabitsch
- Department of Pediatrics and Adolescent Medicine, Ulm University Hospital, Ulm, Germany
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Michael I. Love
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- * E-mail:
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Currin KW, Erdos MR, Narisu N, Rai V, Vadlamudi S, Perrin HJ, Idol JR, Yan T, Albanus RD, Broadaway KA, Etheridge AS, Bonnycastle LL, Orchard P, Didion JP, Chaudhry AS, Innocenti F, Schuetz EG, Scott LJ, Parker SCJ, Collins FS, Mohlke KL. Genetic effects on liver chromatin accessibility identify disease regulatory variants. Am J Hum Genet 2021; 108:1169-1189. [PMID: 34038741 PMCID: PMC8323023 DOI: 10.1016/j.ajhg.2021.05.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 05/04/2021] [Indexed: 02/02/2023] Open
Abstract
Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
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Affiliation(s)
- Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Vivek Rai
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Hannah J Perrin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jacqueline R Idol
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tingfen Yan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lori L Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amarjit S Chaudhry
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Erin G Schuetz
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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Affiliation(s)
- Federico Innocenti
- Federico Innocenti, MD, PhD, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
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